使用卷积神经网络和ISSA检查水文变化及其对水资源短缺趋势及其对水能生产的影响
Xiaofei Liu1, Gang Xuan2, Jafar Safarzadeh3,4
1School of Computer and Information, Anqing Normal University, Anqing, 246133, Anhui, China.
Scientific reports
|October 28, 2025
概括
气候变化和工业增长正在增加干旱的严重程度,影响水力发电. 先进的模型预测更频繁的干旱和更低的水库水位,需要适应性水能管理,以实现可持续的水电计划.
科学领域:
- 环境科学 环境科学
- 气候科学 气候科学
- 水文学的水文学
背景情况:
- 气候变化和工业扩张对水资源构成重大威胁,尤其影响发电.
- 缺乏足够的水资源是可持续能源生产日益关注的问题.
研究的目的:
- 预测未来的气候变化及其对水力发电用水供应的影响.
- 开发一个可靠的模型来预测水库容量波动.
- 为可持续的水电计划策略提供信息.
主要方法:
- 利用全球循环模型 (GCMs) 进行气候变化预测.
- 采用标准化降水指数 (SPI) 来评估干旱的严重程度.
- 开发了一个优化的卷积神经网络 (CNN) 模型来模拟水库动力学.
主要成果:
- 预计在2025-2035年期间,水文变异性将增加,干旱将更加频繁和严重 (SPI值<-1.5).
- 显示了近期潮湿的情况 (2024-2026,2034-2036),SPI值> +1.0.0.
- 在模拟水库动态方面,CNN模型表现出高精度 (R2=0.89,NSE=0.80).
- 预计水电发电将在2026年左右达到峰值,随后在某些气候情景下下降 (SSP5).
结论:
- 增加的水文变异性需要适应性水能管理策略.
- 准确预测水库动态对于可持续的水电计划至关重要.
- 气候变化对可靠的水电发电构成重大风险.
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